An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

A long-span Prestressed Concrete Hunched Beam with Multi-Opening has been developed as an alternative to steel structural elements. The commercial finite element package ABAQUS/CAE version 2019 has been utilized. This article has presented the results of three-dimensional numerical simulations investigating the flexural behaviour of existing experimental work of supported Prestressed Concrete Hunched Beams with multiple openings of varying shapes under static monotonic loads. Insertion openings in such a beam lead to concentrate stresses at the corners of these openings; as a result, extensive cracking would appear. Correlation between numerical models and empirical work has also been discussed regarding load displacemen

The adsorption behavior of Bismarck brown (BB) dye from aqueous solutions onto graphene oxide GO and graphene oxide-g-poly (n-butyl methacrylate-co-methacrylic acid) GO-g-pBCM as adsorbents was investigated. The prepared GO and GO-g-pBCM were characterized by Fourier transform infrared spectroscopy FTIR, which confirmed the compositions of the prepared adsorbents. Adsorption of BB dye onto GO and GO-g-pBCM was explored in a series of batch experiments under various conditions. The data were examined utilizing Langmuir and Freundlich isotherms. The Langmuir isotherm was seen as increasingly reasonable from the experimental information of dye on formulating adsorbents. Kinetic investigations showed that the experimental data were fitted ve

Regression models are among the most important tools in scientific research and data analysis. Among these models, fuzzy regression models stand out as a modern form that addresses issues of uncertain data that do not conform to the assumptions of traditional models. In this study, we present fuzzy regression models with a focus on fuzzy linear quantitative models, in addition to fuzzy support vector machine (SVM) models. Generally, linear models are considered less effective compared to non-linear models, and to address this issue, hybrid models combining both types have been introduced. The concept of hybrid models has been generalized to fuzzy models in this paper, where we introduce a hybrid model that combines both linear and non-linea

—Fundus images play an essential role in ophthalmic diagnostics for the detection of many eye illnesses. The experiment begins with a thorough image preprocessing. technique, which includes clipping the circular borders, scaling the image, enhancing the contrast, removing noise, and augmenting the data. The new combined block applies to extracting distinctive deep feature representations, which help to detect the first shape of the edges of each lesion. It is namely the Attention Block and the Conv-Deconv UNET model. The attention block is subsequently implemented in order to augment the robustness and quality of feature depictions derived from a pair of DR images. The Dual Attention Block for the backbone, which is supplement

In this thesis, we introduced the simply* compact spaces which are defined over simply* open set, and study relation between the simply* separation axioms and the compactness were studied and study a new types of functions known as αS^(M* )- irresolte , αS^(M* )- continuous and R S^(M* )- continuous, which are defined between two topological spaces. On the other hand we use the class of soft simply open set to define a new types of separation axioms in soft topological spaces and we introduce the concept of soft simply compactness and study it. We explain and discuss some new concepts in soft topological spaces such as soft simply separated, soft simply disjoint, soft simply division, soft simply limit point and we define soft simply c

 Abstract

An experimental study was conducted for measuring the quality of surface finishing roughness using magnetic abrasive finishing technique (MAF) on brass plate which is very difficult to be polish by a conventional machining process where the cost is high and much more susceptible to surface damage as compared to other materials. Four operation parameters were studied, the gap between the work piece and the electromagnetic inductor, the current that generate the flux, the rotational Spindale speed and amount of abrasive powder size considering constant linear feed movement between machine head and workpiece. Adaptive Neuro fuzzy inference system  (ANFIS) was implemented for evaluation of a serie

In the beta decay process, a neutron converts into a proton, or vice versa, so the atom in this process changes to a more stable isobar. Bethe-Weizsäcker used a quasi-experimental formula in the present study to find the most stable isobar for isobaric groups of mass nuclides (A=165-175). In a group of isobars, there are two methods of calculating the most stable isobar. The most stable isobar represents the lowest parabola value by calculating the binding energy value (B.E) for each nuclide in this family, and then drawing these binding energy values as a function of the atomic number (Z) in order to obtain the mass parabolas, the second method is by calculating the atomic number value of the most stable isobar (ZA). The results show